Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
405385 | Knowledge-Based Systems | 2008 | 6 Pages |
Abstract
Finding previously unknown patterns in a time series has received much attention in recent years. Of the associated algorithms, the k-motif algorithm is one of the most effective and efficient. It is also widely used as a time series preprocessing routine for many other data mining tasks. However, the k-motif algorithm depends on the predefine of the parameter w, which is the length of the pattern. This paper introduces a novel k-motif-based algorithm that can solve the existing problem and, moreover, provide a way to generate the original patterns by summarizing the discovered motifs.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Heng Tang, Stephen Shaoyi Liao,